Abstract
In the current scenario of the world, digitalization looks expanding ubiquity as a result of consistent, helpful and advantageous utilization of e-commerce. It has demonstrated to be a slam gasp and simple method of installment passage. Purchasers pick online installment and e-shopping, due to time comfort. Because of this, an enormous measure of online business use, there is an immense addition in credit card frauds moreover. Fraudsters attempt to abuse the card and straightforwardness of online installments. To beat the fraudster’s action become fundamental, the primary point is to verify credit card transactions; in this way, individuals can utilize e-exchanges securely and effectively. To identify the charge card misrepresentation, there are different methods which depend on deep learning, logistic regression, naïve Bayesian, support vector machine (SVM), neural network, artificial immune system, nearest neighbor, data mining, decision tree, fuzzy logic-based system, genetic algorithm and so on.
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Parmar, J., Patel, A., Savsani, M. (2021). A Novel Approach for Credit Card Fraud Detection Through Deep Learning. In: Kotecha, K., Piuri, V., Shah, H., Patel, R. (eds) Data Science and Intelligent Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 52. Springer, Singapore. https://doi.org/10.1007/978-981-15-4474-3_22
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DOI: https://doi.org/10.1007/978-981-15-4474-3_22
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